Connect classical quality engineering with auditable agentic systems. Use PACTS to make quality work observable, contextual, and accountable.
Five principles for applying agentic systems without abandoning context-driven quality engineering. PACTS makes boundaries, evidence, and human judgment explicit.
Test before bugs; design testability into the architecture. Shift from reactive firefighting to proactive quality design.
Teams and agents own quality and decide within boundaries (guardrails), executing, learning, and adapting without constant human intervention.
Whole-team quality. Humans and agents work together — quality becomes a true team sport.
Risk-focused; test what matters, skip what doesn't. Value-driven quality that delivers business impact.
Governance, observability, and explainability of agent behavior — especially where decisions must be reconstructed and challenged. Structure prevents teams from bolting agentic AI onto existing chaos.
Start with the smallest engagement that can produce useful evidence.
Map the product, quality risks, delivery constraints, and places where agentic assistance could earn its way in.
Test one valuable use case against an agreed baseline before scaling tools, agents, or organizational change.
A hands-on learning format built around your systems, risks, and existing engineering practices.
A practical bridge between established QE judgment and an open-source portfolio—not a single framework statistic.
We will start with context, identify the decision that matters, and agree what evidence would justify the next step.
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